DataManager.py

import os
import sys
import math
import tarfile


class DataManager:
    def __init__(self, dataset_path):
        self.dataset_path = dataset_path

    def extract_dataset(self, compressed_dataset_file_name, dataset_directory):
        try:
            # extract files to dataset folder
            tar = tarfile.open(compressed_dataset_file_name, "r:gz")
            tar.extractall(dataset_directory)
            tar.close()
            print("Files extraction was successfull ...")

        except:
            print("Ecxception raised: No extraction was done ...")

    def make_folder(self, folder_path):
        try:
            os.mkdir(folder_path)
            print(folder_path, "was created ...")
        except:
            print("Ecxception raised: ", folder_path, "could not be created ...")

    def move_files(self, src, dst, group):
        for fname in group:
            os.rename(src + '/' + fname, dst + '/' + fname)

    def get_fnames_from_dict(self, dataset_dict, f_or_m):
        training_data, testing_data = [], []

        for i in range(1,5):
            length_data       = len(dataset_dict[f_or_m +"000" + str(i)])
            length_separator  = math.trunc(length_data*2/3)

            training_data += dataset_dict[f_or_m + "000" + str(i)][:length_separator]
            testing_data  += dataset_dict[f_or_m + "000" + str(i)][length_separator:]

        return training_data, testing_data

    def manage(self):

        # read config file and get path to compressed dataset
        compressed_dataset_file_name = self.dataset_path
        dataset_directory = compressed_dataset_file_name.split(".")[0]

        # create a folder for the data
        try:
            os.mkdir(dataset_directory)
        except:
            pass

        # extract dataset
        self.extract_dataset(compressed_dataset_file_name, dataset_directory)

        # select females files and males files
        file_names   = [fname for fname in os.listdir(dataset_directory) if ("f0" in fname or "m0" in fname)]
        dataset_dict = {"f0001": [], "f0002": [], "f0003": [], "f0004": [], "f0005": [],
                        "m0001": [], "m0002": [], "m0003": [], "m0004": [], "m0005": [], }

        # fill in dictionary
        for fname in file_names:
            dataset_dict[fname.split('_')[0]].append(fname)

        # divide and group file names
        training_set, testing_set = {},{}
        training_set["females"], testing_set["females"] = self.get_fnames_from_dict(dataset_dict, "f")
        training_set["males"  ], testing_set["males"  ] = self.get_fnames_from_dict(dataset_dict, "m")

        # make training and testing folders
        self.make_folder("TrainingData")
        self.make_folder("TestingData")
        self.make_folder("TrainingData/females")
        self.make_folder("TrainingData/males")
        self.make_folder("TestingData/females")
        self.make_folder("TestingData/males")

        # move files
        self.move_files(dataset_directory, "TrainingData/females", training_set["females"])
        self.move_files(dataset_directory, "TrainingData/males",   training_set["males"])
        self.move_files(dataset_directory, "TestingData/females",  testing_set["females"])
        self.move_files(dataset_directory, "TestingData/males",    testing_set["males"])


if __name__== "__main__":
    data_manager = DataManager("SLR45.tgz")
    data_manager.manage()